arXiv:1803.07461
Speech-Driven Facial Reenactment Using Conditional Generative Adversarial Networks
원문 초록
We present a novel approach to generating photo-realistic images of a face with accurate lip sync, given an audio input. By using a recurrent neural network, we achieved mouth landmarks based on audio features. We exploited the power of conditional generative adversarial networks to produce highly-realistic face conditioned on a set of landmarks. These two networks together are capable of producing a sequence of natural faces in sync with an input audio track.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Not made for each other- Audio-Visual Dissonance-based Deepfake Detection and Localization
Real-Time Lip Sync for Live 2D Animation
Dynamic Temporal Alignment of Speech to Lips
Talking Face Generation by Conditional Recurrent Adversarial Network
A Neural Lip-Sync Framework for Synthesizing Photorealistic Virtual News Anchors
DeepFakes: a New Threat to Face Recognition? Assessment and Detection
토론
이 논문과 연결된 포럼 글이 아직 없습니다.